Image processing of digital images often avoids complex image processing operations that yield high image quality in favor of faster image processing operations that yield inferior image quality. The net result is that most commercially available image processing packages offer less than optimal image quality performance because to achieve said performance would be prohibitive from a processing time perspective.
If speed or memory constraints were not an issue, the complex image processing operation would be run exclusively. For many images, only the complex image processing operation can yield high image quality. However, on a significant subset of images, the application of a complex image processing operation does not produce significant improvement in image quality over a faster image processing operation. It would therefore be valuable to have a mechanism for applying the more complex image processing operations for only the images that would see improved image quality to obtain the maximum value while not adversely affecting the average system throughput.
U.S. patent application Ser. No. 10/178,260, filed Jun. 24, 2002 by Gindele et al., hereby incorporated herein by reference, describes a method for generating a one-dimensional look-up table for improving the tone scale of an input digital image. This tone scale can then be applied directly to the three color channels, or can be applied solely to a low-frequency sub band of the luminance channel. The former approach is fast, but achieves poor image quality when the one-dimensional look-up table has a low slope. The latter approach is slow, but achieves high image quality when the one-dimensional look-up table has a low slope. By inspecting the slope of the one-dimensional look-up table, a decision can be made as to which enhancement algorithm technique to use. For images with very low or high slopes, this decision is straightforward. For slopes in the middle, this decision is difficult and likely to result in objectionable artifacts if the wrong choice is made.
U.S. Pat. No. 5,694,484, to Cottrell et al., describes a method of building an image processing system with an automated intelligent control mechanism for controlling a collection of algorithms and adjustable parameters. The determination of which algorithm or what parameters is based upon predictor values that are calibrated in controlled psychophysical experiments. The end result is images of high quality. This approach has the shortcoming of being complex and can result in discrete and distinct levels of image quality as different algorithms are switched on and off.
Many different types image enhancements have algorithms and functions that differ in speed and quality.
The contrast and lightness characteristics of digital images are commonly enhanced through the application of a tone scale curve. For a generalized tone scale curve f( ), the input pixel value x is transformed to an output pixel value f(x). The shape of the tone scale curve determines the visual effect imparted to the processed digital image. Some tone scale curves applied to digital images are independent of the pixel values in the digital image to be processed. For example, image independent tone scale curves can be useful for establishing a photographic look to processed digital images. While image independent tone scale curves can be used to enhance many digital images, digital images that are either too high or low in contrast can benefit from the application of a tone scale curve that is responsive to the distribution of pixel values in the digital image to be processed. For image dependent tone scale curves, the mathematical formula used to generate the function f(x) determines the degree and nature of the image enhancement.
U.S. Pat. No. 6,285,798, to Lee, which is hereby incorporated herein by reference, discloses a method of generating a tone scale curve for the purposes of reducing the dynamic range of a digital image. The tone scale curve construction method establishes six constraints and then performs a successive integration procedure to satisfy the constraints. U.S. patent application Ser. No. 10/178,260, to Gindele, which is hereby incorporated herein by reference, describes generation of a tone scale function having a highlight tone scale segment and a shadow tone scale segment.
Image enhancement algorithms are well known that apply a tone scale function directly to the red, green, blue (RGB) color planes of a digital image. These algorithms produce images of generally quite high quality, but have the shortcoming of a tendency to reduce texture in some images.
U.S. Pat. No. 5,012,333, to Lee et al., which is hereby incorporated herein by reference, discloses an image enhancement algorithm, which applies a tone scale function to a low frequency sub-band of the image, while preserving higher frequency sub-bands that are considered image texture. U.S. Pat. No. 6,317,521, to Gallagher et al., which is hereby incorporated herein by reference, discloses a similar algorithm, which incorporates an artifact avoidance scheme along with a single standard Finite Impulse Response (FIR) filter to generate the texture signal, in order to reduce the occurrence of artifacts in the final image. U.S. patent application Ser. No. 10/607,401, by Gallagher, which is hereby incorporated herein by reference, describes a method of applying highly compressive tone scale functions to digital images by processing a digital image to form an image pyramid having multiple image levels. These algorithms produce images of high quality while largely preserving texture, but are quite computationally expensive to run in comparison to applying a tone scale function directly to the RGB color planes. Other examples of tone scale functions and algorithms disclosed in U.S. patent application Ser. No. 10/246,856, filed Sep. 19, 2002; Ser. No. 10/263,113, filed Oct. 2, 2002; and Ser. No. 10/280,369, filed Oct. 25, 2002, all of which are hereby incorporated herein by reference.
It is well known to apply color corrections uniformly to an image. On the other hand, “Methods to Reduce the Amplification of Random Noise in the Color Processing of Imager Data”, McCleary, IS&T's 2003 PICS Proceedings, pp. 50-57 teaches that applying color correction to sufficiently noisy images will result in superior image quality if more accurate color correction functions are applied to the low frequency sub-band of the image while less accurate or unity (no change) color correction functions are applied to the higher frequency bands of the image.
Different noise filters are well known, as are different algorithms that apply noise filters. U.S. patent application Ser. No. 10/151,623, filed May 20, 2002, by Gindele, which is hereby incorporated herein by reference, discloses a method of computing a noise estimate for a digital image, which uses gradient analysis on the source digital image and pixels in a plurality of orientations to calculate a noise characteristic value. U.S. patent application Ser. No. 09/742,957, filed Dec. 21, 2000, by Gindele, which is hereby incorporated herein by reference, discloses a method that allows customized noise filtering of both basis and texture images at each level of a multi-resolution or pyramidal resolution series containing a single low resolution basis image and a series of texture images of increasing resolution. Alternatively, one can form a luminance chrominance pyramid. Typical filtering operations at each pyramid level include sigma filtering and median filtering.
It would thus be desirable to provide improved image enhancement methods, systems, and computer program products, which regulate speed vs. image quality tradeoffs so as to reduce objectionable artifacts and increase overall image quality.